Key drivers of global change threaten biodiversity worldwide, and accurate and cost-efficient methods for assessing biodiversity at multiple spatial scales are increasingly needed. Remote sensing offers myriad possibilities for assessing biodiversity at local to global scales. However, for most taxa, there have been relatively few studies examining linkages between remote sensing metrics and biodiversity. Moreover, the efficacy of many remote sensing techniques for biodiversity estimation and monitoring has not been thoroughly examined to date.

This session will focus on how remote sensing may be used to monitor, model, and predict biodiversity across taxa and spatial scales. We invite talks on a variety of topics including inferring taxonomic, structural, or functional diversity from remote sensing metrics; mechanisms linking remotely sensed environmental variables or vegetation traits to biodiversity; data fusion to improve biodiversity estimation and species distribution models; and other novel applications of remotely sensed data for biodiversity assessments.

• GC - Global Environmental Change